title: A population-based validation of the prognostic model PREDICT for early breast cancer.
abstract: BACKGROUND
  Predict (www.predict.nhs.uk) is a prognostication and treatment benefit tool developed using UK cancer registry data. The aim of this study was to compare the 10-year survival estimates from Predict with observed 10-year outcome from a British Columbia dataset and to compare the estimates with those generated by Adjuvant! (www.adjuvantonline.com).
  
  
  METHODS
  The analysis was based on data from 3140 patients with early invasive breast cancer diagnosed in British Columbia, Canada, from 1989-1993. Demographic, pathologic, staging and treatment data were used to predict 10-year overall survival (OS) and breast cancer specific survival (BCSS) using Adjuvant! and Predict models. Predicted outcomes from both models were then compared with observed outcomes.
  
  
  RESULTS
  Calibration of both models was excellent. The difference in total number of deaths estimated by Predict was 4.1 percent of observed compared to 0.7 percent for Adjuvant!. The total number of breast cancer specific deaths estimated by Predict was 3.4 percent of observed compared to 6.7 percent for Adjuvant! Both models also discriminate well with similar AUC for Predict and Adjuvant! respectively for both OS (0.709 vs 0.712) and BCSS (0.723 vs 0.727). Neither model performed well in women aged 20-35.
  
  
  CONCLUSIONS
  In summary Predict provided accurate overall and breast cancer specific survival estimates in the British Columbia dataset that are comparable with outcome estimates from Adjuvant! Both models appear well calibrated with similar model discrimination. This study provides further validation of Predict as an effective predictive tool following surgery for invasive breast cancer.
authors.affiliation: Cambridge Breast Unit, Addenbrooke's Hospital, Hills Road, Cambridge, CB2 2QQ, UK.
authors.forename: G C
authors.initials: GC
authors.lastname: Wishart
authors.forename: C D
authors.initials: CD
authors.lastname: Bajdik
authors.forename: E M
authors.initials: EM
authors.lastname: Azzato
authors.forename: E
authors.initials: E
authors.lastname: Dicks
authors.forename: D C
authors.initials: DC
authors.lastname: Greenberg
authors.forename: J
authors.initials: J
authors.lastname: Rashbass
authors.forename: C
authors.initials: C
authors.lastname: Caldas
authors.forename: P D P
authors.initials: PD
authors.lastname: Pharoah
mesh_terms: D000328:Adult; D000368:Aged; D001943:Breast Neoplasms / Q000175:diagnosis* / Q000401:mortality* / Q000473:pathology / Q000628:therapy; D001955:British Columbia / Q000453:epidemiology; D018270:Carcinoma, Ductal, Breast / Q000175:diagnosis / Q000401:mortality; D018275:Carcinoma, Lobular / Q000175:diagnosis / Q000401:mortality; D005260:Female; D006801:Humans; D020407:Internet; D008875:Middle Aged; D015233:Models, Statistical; D009367:Neoplasm Staging; D011237:Predictive Value of Tests; D011379:Prognosis; D012372:ROC Curve; D012042:Registries; D015996:Survival Rate; D006113:United Kingdom